Schemas determine what we learn

I’m teaching the class about a poem we’ve read. I tell them the poet is writing about love. But instead of writing ‘love’, the poet uses a different word… a euphemism for love. The poet has repeated the same line with the euphemism in it across every verse.

“Why have they done this year 10? Write down your answer.”

I walk around the room.

Some pupils seem to ‘get’ what I’m saying. They’re writing about the poet being in denial, or afraid… the use of repetition reaches a crescendo reflecting the poet’s desperation to say how they feel.

But other pupils are writing generically: the poet is using repetition to emphasise something or other.

And some pupils have totally misunderstood: they say the poet isn’t really in love or they’d just say so.

Why is this happening?

One major reason: there is a big difference in the quality of pupils’ prior knowledge.*

And relevant prior knowledge is crucial for learning.

In this blog we are going to talk about prior knowledge in terms of networks of related, stored knowledge in schemas (Fernández & Morris., 2018; Ghosh & Gilboa, 2014; Sekeres et al., 2018).**

Schemas house our prior knowledge of a topic.

But they do much more than that. The quality of our schemas (how much knowledge and how well connected) plays a huge role in what we attend to and learn in a given situation.

My hunch: once we know how crucial schemas are to learning, we won’t be able to stop thinking about them. We’ll –

  • Discuss them in curriculum and lesson planning.
  • Check the quality of them before we teach.
  • Be painstaking about activating the right knowledge before teaching new material.
  • Never wonder why some pupils don’t ‘get it’ again.

Schemas determine what we focus on

Two teachers, one with expertise managing a classroom and the other who is relatively novice, sit down to watch video clips of a classroom.

In some video clips, pupils appear disengaged but not disruptive. In other clips, disruptive behaviour is derailing the lesson.

Despite viewing the same clips, eye-tracking technology shows the two teachers focus on different things:

The novice teacher focuses on unimportant details like a pupil’s fluorescent shoelaces. When there is disruption, the novice teacher focuses mainly on the pupil creating the disruption.

In contrast, the expert focuses on areas that provide them with information about the unfolding situation. Expert teachers don’t fixate on the disruption; they look at the effect on surrounding pupils (Wolff et al., 2016).

How can two people view the same scenes so differently?

The answer:

Our schemas determine what we attend to.

Experts have rich, well-organised schemas that allow them to focus on the meaningful aspects of situations because they know they are meaningful. ***

But why do schemas focus us on just some information in the environment?

Our brains want to update what we already know

Schemas represent our brain’s best attempt to collate important knowledge from across many experiences. Important knowledge that can help us make accurate predictions in new situations.

Keeping schemas up-to-date is therefore a priority. It allows us to continue to make accurate predictions.

To do this, the brain focuses on learning new information that is relevant to our existing schemas (Kurashige et al., 2019): not exactly the same but at least relevant to what we know.****

You might sense upsides and downsides here:

Upside: the brain tries to build upon what it knows.

Downside: learning is limited by the quality of our schemas. Hence why the novice teacher isn’t able to focus on the more important aspects of the classroom on their own.

Let’s look more closely at what’s happening in the brain.

Our brains are selective about what we learn

Relevant schemas come to mind in a matter of milliseconds to help us make sense of what we are experiencing (Gilboa & Moscovitch, 2017; Rourke et al., 2016).

But some research suggests schemas act even sooner than that…

Our brains may assemble patterns of brain activity that stand ready to encode and learn information before we’ve even seen the new information (Kurashige et al., 2018; Sadeh et al., 2018).

The shape of these patterns may be influenced by what we already know of a topic (our prior knowledge). Think of these patterns like neural scaffolds (Sadeh et al., 2018) put in place by our brains to make it easier to build new knowledge… but only if it relates to what we already know.

So, what happens when we encounter the new information?

Our brains reinstate these patterns of brain activity influenced by prior knowledge (our neural scaffolds). They reinstate them strongly when they overlap with the neural pattern of the new, incoming information. This makes this new information easier to encode and learn (Kurashige et al., 2018).

By making it easier to learn something that overlaps with a pattern of brain activity that already exists, the brain is selectively updating our knowledge.

In short:

  • Even before our brains encounter new information, they lay down neural scaffolds, i.e. patterns of brain activity shaped by our prior knowledge.
  • These patterns reinstate themselves during encoding of new information.
  • Where these patterns are similar to the patterns of incoming information, this information can be more easily encoded and learned.
  • This is our brains using what we know to select what to learn.

What might this mean for teachers?

(1) Plan for a stream of thought

What pupils think about before new information is introduced affects how well it is learned. This means the goal is not just about getting pupils to think hard during singular lesson tasks. It’s about creating a stream of thought throughout the lesson and across lessons.

To me, this highlights why the best lessons may stem from curricula where content and sequencing have been carefully conceived.

In lessons, this stream of thought is created through tasks that focus pupils’ thinking on the knowledge they need to learn.

Here’s a non-example:

I set up an activity where pupils have to roll dice and answer the question that corresponds to the number on the die. Pupils spend ages thinking about where their die has rolled off to instead of thinking about the questions.

If we view planning lessons as both a content problem (what do I want pupils to learn/what do I include in this lesson?) and an implementation problem (how do I design/execute the lesson so pupils learn it?) we can see where I went wrong. I let the implementation (the design of the task) interfere with learning the content.

Don’t let the implementation interfere with learning the content.

Always ask yourself: in this task, how can I make sure pupils have to think about the meaning of this information? (Willingham, 2003).

(2) Activate and link to prior knowledge

Patterns of brain activity before new material is even seen, influence learning. They act like neural scaffolds.

Set the scene for new learning by activating useful prior knowledge before introducing new material.

Think of me teaching the poem (beginning of this blog).

I wanted pupils to realise the poet was in denial/afraid to say they were in love. I should activate those ideas first by talking about love as a powerful and risky emotion that can be difficult to admit. Then help pupils draw the connection to the poem. This will help pupils understand this particular meaning.*****

Nothing we teach is inherently meaningful. Meaning is made in the interaction between the material we teach and the knowledge pupils already have (Ausubel, 2012).

We need to explicitly ensure the connection happens.

(3) Be explicit

Our brains selectively update based on what we already know. This means, if pupils don’t know very much about a topic, it’s highly unlikely they will attend to, encode and learn the important information without explicit instruction.

Think of it this way…

Pupils don’t learn what you teach; they learn their interpretation of what you teach.

For pupils lacking in knowledge of a topic, this means they can totally miss the meaning you want them to make from a text/example/demonstration/explanation unless you explicitly tell them what to focus on.

Leave no gaps.

This relates to the brilliant work on the importance of fully-guided instruction (Kirschner et al., 2006).

(4) Fade scaffolds

In English I used to make pupils practise using an acronym to help them spot language techniques in texts. I thought it was a helpful scaffold for them because soon they could pick out language techniques pretty easily from texts. But then I realised that whenever they encountered a text, spotting language techniques was about all they could do. The scaffold became the schema.

Don’t let the scaffold become the schema.

This doesn’t mean we shouldn’t use scaffolds. It means we must monitor them and gradually fade their usage before they limit what pupils attend to.

Now we know prior knowledge is crucial to learning. It affects how quickly pupils learn new information and as we’ve seen in this blog, it actually affects what pupils attend to and interpret from your lessons too.

*This needn’t be the only reason but it’s probably a prevalent one.

**There are lots of definitions of schema out there (e.g., Bartlett, 1932; Fernández & Morris., 2018; Ghosh & Gilboa., 2014; van Kesteren et al., 2012). I’ve chosen some common elements and created a simplified definition.

***There’s some interesting research on the sophisticated perception of experts as an adaptation based on the fine-tuning of visual neurons. Experts in the visual perception of an environment have, through a top-down process, sensitised the neurons that usually only engage in automatic gist processing, so that they automatically attend to relevant stimuli in that environment (Ahissar & Hochstein, 2004). What would take novices greater attentional resource to perceive and comprehend (assuming they had the knowledge to do so), is processed automatically by experts.

****You might be thinking, hang on a sec, why do I seem to focus/remember stuff that surprises me though? I don’t know that stuff! To experience surprise, you must already know something about the thing in the first place in order to make a prediction that doesn’t come true (van Kesteren et al., 2012). Hence the brain is updating based on what it already knows. Highly novel events though, whilst stored, are thought to be stored differently (by the hippocampus as an episodic memory rather than entering the neocortex/schemas) (Alonso et al., 2020).

*****There are many subjects, English included, where we want pupils to come to their own interpretation of texts. I would argue (along with many smarter people than me), that this can only happen with a lot of domain-specific knowledge and explicitly teaching them common interpretations to start with is vital to this.


Alonso, A., van der Meij, J., Tse, D., & Genzel, L. (2020). Naïve to expert: considering the role of previous knowledge in memory. Brain and neuroscience advances4, 2398212820948686.

Ausubel, D. P. (2012). The acquisition and retention of knowledge: A cognitive view. Springer Science & Business Media.

Fernández, G., & Morris, R. G. (2018). Memory, novelty and prior knowledge. Trends in Neurosciences, 41(10), 654-659.

Ghosh, V. E., & Gilboa, A. (2014). What is a memory schema? A historical perspective on current neuroscience literature. Neuropsychologia, 53, 104-114.

Gilboa, A., & Moscovitch, M. (2017). Ventromedial prefrontal cortex generates pre-stimulus theta coherence desynchronization: a schema instantiation hypothesis. Cortex, 87, 16-30.

Kirschner, P. A., Sweller, J., & Clark, R. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential and inquiry-based teaching. Educational Psychologist, 41, 75–86.

Kurashige, H., Yamashita, Y., Hanakawa, T., & Honda, M. (2018). A knowledge-based arrangement of prototypical neural representation prior to experience contributes to selectivity in upcoming knowledge acquisition. Frontiers in human neuroscience, 12, 111.

Kurashige, H., Yamashita, Y., Hanakawa, T., & Honda, M. (2019). Effective Augmentation of Creativity-Involving Productivity Consequent to Spontaneous Selectivity in Knowledge Acquisition. Frontiers in Psychology, 10, 600.

Rourke, L., Cruikshank, L. C., Shapke, L., & Singhal, A. (2016). A neural marker of medical visual expertise: implications for training. Advances in Health Sciences Education, 21(5), 953-966.

Sadeh, T., Chen, J., Goshen-Gottstein, Y., & Moscovitch, M. (2018). Spontaneous Pre-encoding Activation of Neural Patterns Predicts Memory. bioRxiv, 229401.

Sekeres, M. J., Winocur, G., & Moscovitch, M. (2018). The hippocampus and related neocortical structures in memory transformation. Neuroscience letters, 680, 39-53.

van Kesteren, M. T., Rijpkema, M., Ruiter, D. J., & Fernández, G. (2010). Retrieval of associative information congruent with prior knowledge is related to increased medial prefrontal activity and connectivity. Journal of Neuroscience, 30(47), 15888-15894.

van Kesteren, M. T., Ruiter, D. J., Fernández, G., & Henson, R. N. (2012). How schema and novelty augment memory formation. Trends in neurosciences, 35(4), 211-219.

Willingham, D. (2003). Ask the Cognitive Scientist: Students Remember…What They Think About. [Article] Available from

Wolff, C. E., Jarodzka, H., van den Bogert, N., & Boshuizen, H. (2016). Teacher vision: Expert and novice teachers’ perception of problematic classroom management scenes. Instructional Science, 44(3), 243-265.

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